CIO Business Intelligence

NOVEMBER 14, 2022

With organizations increasingly focused on data-driven decision making, decision science (or decision intelligence) is on the rise, and decision scientists may be the key to unlocking the potential of decision science systems. Optimization analysis models. Analytics, Data Science Model-driven DSS.

Data mining 144

Data mining Data-driven Statistics OLAP 144

CIO Business Intelligence

APRIL 25, 2022

“You can think that the general-purpose version of the Databricks Lakehouse as giving the organization 80% of what it needs to get to the productive use of its data to drive business insights and data science specific to the business. Features focus on media and entertainment firms.

Recreation/Entertainment 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

AWS Big Data

AUGUST 2, 2023

This post was co-written by Sheel Saket, Senior Data Science Manager at FIS, and Rupesh Tiwari, Senior Architect at Amazon Web Services. The workflow includes the following steps: GitHub webhook events stream data to both Amazon S3 and OpenSearch Service, facilitating real-time data analysis. Want to know more?

Visualization 77

Visualization Insurance Cost-Benefit Finance 77

Smart Data Collective

SEPTEMBER 23, 2020

We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes. Both data warehouses and data lakes are used when storing big data. Many people are confused about these two, but the only similarity between them is the high-level principle of data storing.

Data Lake 106

Data Lake Data Warehouse Unstructured Data Big Data 106

CDW Research Hub

APRIL 20, 2020

Snowflake, a data warehouse built specifically for the cloud, is one popular option. Snowflake helps eliminate many of the common issues data professionals face because it supports structured and semi-structured data, scales massive concurrency without limit, and boasts secure, live data sharing.

Data Warehouse 52

Data Warehouse Consulting Data-driven Structured Data 52

AWS Big Data

JUNE 6, 2023

In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake. AWS Glue gave us a cost-efficient option to migrate the data and we further optimized storage cost by pruning cold data.

Analytics 56

Analytics Data Lake Testing Optimization 56

Ontotext

NOVEMBER 2, 2023

This is partly because integrating and moving data is not the only problem. The data itself is stored in a way that is not optimal for extracting insight. Unlocking additional value from data requires context, relationships, and structure, none of which are present in the way most organizations store their data today.

IT 69

IT Cost-Benefit Data-driven Technology 69

CIO Business Intelligence

MARCH 24, 2023

Data governance principles According to the Data Governance Institute, eight principles are at the center of all successful data governance and stewardship programs: All participants must have integrity in their dealings with each other.

Data Governance 142

Data Governance Management Metadata Data Quality 142

AWS Big Data

MARCH 7, 2023

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. They should also provide optimal performance with low or no tuning. Popular consumption entities in many organizations are queries, reports, and data science workloads.

Analytics 68

Analytics Data Warehouse Data Lake Metadata 68

IBM Big Data Hub

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. Data extraction Once you’ve assigned numerical values, you will apply one or more text-mining techniques to the structured data to extract insights from social media data.

Data mining 59

Data mining Machine Learning Deep Learning Marketing 59

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift enables you to use SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and machine learning (ML) to deliver the best price-performance at scale.

Data Warehouse 89

Data Warehouse Data Lake Analytics Data Science 89

CIO Business Intelligence

MARCH 9, 2022

As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

Cloudera

JULY 26, 2021

Once we have identified those capabilities, the second article explores how the Cloudera Data Platform delivers those prerequisite capabilities and has enabled organizations such as IQVIA to innovate in Healthcare with the Human Data Science Cloud. . Business and Technology Forces Shaping Data Product Development.

Strategy 117

Strategy Data Science Marketing Unstructured Data 117

CIO Business Intelligence

MAY 10, 2022

A customer data platform (CDP) is a prepackaged, unified customer database that pulls data from multiple sources to create customer profiles of structured data available to other marketing systems. It requires SQL for optimal use, so is best suited for data engineers and analysts. Treasure Data CDP.

Advertising 122

Advertising Interactive Marketing Data Integration 122

Cloudera

MAY 17, 2021

Modernizing your data warehousing experience with the cloud means moving from dedicated, on-premises hardware focused on traditional relational analytics on structured data to a modern platform. You need to have the best price/performance to optimize your cost management.

Data Warehouse 90

Data Warehouse Measurement Reporting Testing 90

AWS Big Data

AUGUST 16, 2023

Iceberg manages large collections of files as tables, and it supports modern analytical data lake operations such as record-level insert, update, delete, and time travel queries. Iceberg also helps guarantee data correctness under concurrent write scenarios. Utilize Athena OPTIMIZE command to compact these small files.

Data Lake 68

Data Lake Metadata Testing Snapshot 68

Domino Data Lab

MARCH 3, 2019

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Welcome back to our monthly series about data science! This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

IBM Big Data Hub

JANUARY 10, 2024

Artificial intelligence (AI) refers to the convergent fields of computer and data science focused on building machines with human intelligence to perform tasks that would previously have required a human being. For optimal performance, AI models should receive data from a diverse datasets (e.g.,

Unstructured Data 84

Unstructured Data Deep Learning Cost-Benefit Modeling 84

AWS Big Data

MARCH 26, 2024

With QuickSight, you can embed dashboards to external websites and applications , and the SPICE engine enables rapid, interactive data visualization at scale. Data warehouse Data warehouses are efficient in consolidating structured data from multifarious sources and serving analytics queries from a large number of concurrent users.

Data Strategy 68

Data Strategy Strategy Data Warehouse Prescriptive Analytics 68

CIO Business Intelligence

JUNE 14, 2023

To accomplish this, we will need additional data center space, more storage disks and nodes, the ability for the software to scale to 1000+PB of data, and increased support through additional compute nodes and networking bandwidth. Consider data types. Focus on scalability.

Unstructured Data 64

Unstructured Data IT Manufacturing Visualization 64

The Unofficial Google Data Science Blog

SEPTEMBER 9, 2015

Sawzall is a programming language developed at Google for performing aggregation over the result of complex operations on structured data. However, it turns out to be quite useful for data science applications. But most important to a data science team is how the UDFs are expressed.

Data Science 56

Data Science Statistics Testing Metadata 56

O'Reilly on Data

DECEMBER 19, 2018

We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline. In a previous post , we talked about applications of machine learning (ML) to software development, which included a tour through sample tools in data science and for managing data infrastructure.

Machine Learning 261

Machine Learning Software Testing Metadata 261

Cloudera

APRIL 1, 2024

Cloudera, a leader in big data analytics, provides a unified Data Platform for data management, AI, and analytics. Our customers run some of the world’s most innovative, largest, and most demanding data science, data engineering, analytics, and AI use cases, including PB-size generative AI workloads.

Unstructured Data 106

Unstructured Data Cost-Benefit Metadata Machine Learning 106

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. There are many types of data pipelines, and all of them include extract, transform, load (ETL) to some extent.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52